图片智能识别促销活动

import tensorflow as tf
from tensorflow.keras import layers, models

# 假设我们已经有预处理好的图片数据和标签
train_images = ...  # 训练图片数据
train_labels = ...  # 对应的标签

# 构建卷积神经网络模型
model = models.Sequential([
    layers.Conv2D(32, (3, 3), activation='relu', input_shape=(128, 128, 3)),
    layers.MaxPooling2D((2, 2)),
    layers.Conv2D(64, (3, 3), activation='relu'),
    layers.MaxPooling2D((2, 2)),
    layers.Conv2D(64, (3, 3), activation='relu'),
    layers.Flatten(),
    layers.Dense(64, activation='relu'),
    layers.Dense(10)  # 假设有10类促销标签
])

# 编译模型
model.compile(optimizer='adam',
              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
              metrics=['accuracy'])

# 训练模型
model.fit(train_images, train_labels, epochs=10)

# 使用模型进行预测
predictions = model.predict(test_images)